20 April 2013

Eight Annual Fragment-Based Drug Discovery Meeting (part 2)

The last major fragment event of 2013, CHI’s FBDD, wrapped up earlier this week in San Diego. As with last year this summary is not meant to be comprehensive (and you can also read Teddy’s impressions here.)

The FBDD track is just one of six within the CHI Drug Discovery Chemistry Conference. One indication of the success of the field is its appearance in several of the other tracks: attendees were likely to hear about fragments without going to the FBDD track at all.

In the GPCR track, Robert Cooke from Heptares discussed the application of fragments to the β1-adrenergic receptor (see also here). In the kinase track, Hongtao Zhao presented in silico fragment work (see also here). And in the protein-protein interaction track, David Fry from Roche described a deconstruction of the p53-HDM2 inhibitor RG7112 into its component fragments to see whether the molecule could have been identified from FBLD. RG7112 consists of a central core with four appendages, and although the mono-substituted core was too weak to detect, some of the cores with two substituents could be identified and bound to the protein in the same manner as the parent compound. However, these did tend to be super-sized fragments, with molecular weights in the 300-350 Da range.

Protein-protein interactions were also a theme of Richard Taylor, from the company UCB. They built a sizable fragment library of about 23,000 (mostly commercial) compounds designed to cover molecular frameworks found in known drugs. UCB has invested heavily in SPR technology, and with a stable of four Biacore 3000 instruments could rapidly screen this entire library against a dozen protein-protein interaction targets. Not surprisingly, given the difficulty of this target class, the hit rate was much lower than in conventional fragment screens, averaging just about 1%. What was interesting is that only 964 fragments hit any target – at less than 5%, this is much lower than the roughly 33% hit rate seen in other fragment libraries. Most of these fragments were reasonably specific, though; 908 hit ≤ 8 targets. It will be interesting to see whether anything can be learned about “privileged” protein-protein interaction fragments from this set.

Of course, extracting general trends from collections of fragments is not necessarily straightforward. Teddy has already brought up the difficulties of describing molecular shape; as he pointed out in his presentation, Fsp3 is not the best measure of “three-dimensionality” for several reasons. For example, even toluene has an Fsp3 = 0.14, and while Pete Kenny correctly points out that aromatic molecules do have volume, most chemists would think of this as a very “flat” compound. Principal moment of inertia (PMI) is better, but is harder to calculate. Happily, as Justin Bower described in his presentation, the Beatson Institute is allowing other researchers to use their 3DFIT software to calculate PMI and other properties.

One of the criticisms of 3D fragments is that, as Rod Hubbard pointed out, they can be a “pain in the neck” for chemistry. One solution that researchers at Vernalis took was to do analog work on a simpler molecule, then scaffold-hop back to the original fragment once the SAR was sufficiently understood to justify investment in more challenging chemistry.

Finally, the question of what to do with fragment hits that don’t reproduce in different assays was the topic of at least one breakout discussion and was also extensively discussed by Peter Kutchukian, who presented an analysis of 134 fragment screens using a variety of techniques against 34 different targets at Novartis. Some of this was presented at FBLD 2012, but one interesting finding was that hits from biophysical screens (such as SPR, NMR, or DSF) tended to cluster separately from hits in biochemical assays. Given the number of ways to find fragments, pursuing hits that confirm in both a biochemical and a biophysical method may help to weed out artifacts, though at the risk of increasing false negatives.

Feel free to chime in with your thoughts and impressions, whether or not you were there. And if you are kicking yourself for not attending, next year’s meeting is scheduled to return to San Diego from April 22-25.


Anonymous said...

The Biacore model UCB uses must be 4000!

Anonymous said...

I like your comments on Fsp3. I wonder if you have seen this paper , which looks at 3D methods.

Also aside from the misuse of this metric by some people, there is an interesting paper describing some issues with the Fsp3 paper itself.

Dan Erlanson said...

Thanks for the plane of best fit paper - I'll take a look at it. I did see the correlation inflation paper, which is covered here. It's a good reminder that, as the 3D fragment library consortium prominently displays on their 3DFIT page, "parameters are guidelines."